Salim Hayek, M.D.
Dr. Hayek’s expertise lies in risk prediction, specifically in integrating novel biomarkers from high-throughput technologies such as metabolomics and genomics in clinical practice, with the goal of personalizing patient care and optimizing resource allocation.
- M.D., American University of Beirut
- B.S., Biology, American University of Beirut
Health Services Research & Policy Focus
Collaborating Centers & Programs
What are you thinking about?
Innovation in medicine has lagged behind the exponential improvement in technology, computing power, artificial intelligence, and big data. Despite our growing ability to measure, collect and store data at the exabyte scale, we still practice Medicine with the rudimentary tools and cookie-cutter approaches, lumping patients in large categories that simplify very complex pathophysiologies. My research interest is in combining the power of big data analytics, high throughput technologies such as metabolomics and genomics, and the principles of human design to provide healthcare providers and patients the necessary information to personalize therapy at the individual level, optimize resource allocation at the system level, and allowing for a more lean and efficient healthcare system.
Why is this interesting to you?
There is a tremendous opportunity to transform healthcare. The tools to improve our health at both the individual and the system level are available but not effectively used. I enjoy working with specialists from various backgrounds, from biological and data scientists to policy makers, healthcare providers and patients themselves to design and implement strategies that will transform healthcare.
What are the practical implications for healthcare?
Personalizing care can improve outcomes by prescribing therapies at doses that would benefit patients the most and minimize side effects. Similarly, accurately assessing risk will allow us to divert healthcare resources to areas and patients that need it the most. Changing the way we practice medicine doesn’t necessarily require need to be expensive or require high cost drugs or devices, and can rely on adopting available data and technologies more effectively.